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Black bone MRI with 3D reconstruction for the detection of skull fractures in children with suspected abusive head trauma.

Accepted version
Peer-reviewed

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Article

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Authors

Kralik, Stephen F 
Supakul, Nucharin 
Wu, Isaac C 
Delso, Gaspar 
Radhakrishnan, Rupa 

Abstract

PURPOSE: The purpose of this study was to determine the accuracy of "black bone" (BB) MRI for the detection of skull fractures in children with potential abusive head trauma. METHODS: A total of 34 pediatric patients were evaluated for potential abusive head trauma. All patients had both a non-contrast head CT (HCT) with multiplanar reformatted images and 3D volumetric reformatted images where available (gold standard) for fracture diagnosis and BB of the head with multiplanar reformatted images and 3D volumetric images. BB was performed using an ultrashort TE pointwise encoding time reduction with radial acquisition (PETRA) sequence at 1.5 T or 3 T. BB datasets were post-processed and 3D images created using Fovia's High Definition Volume Rendering® software. Two board-certified pediatric neuroradiologists independently reviewed the HCT and BB imaging, blinded to the findings from the other modality. RESULTS: Median patient age was 4 months (range 1.2-30 months). A total of 20 skull fractures in six patients (18% incidence of skull fractures) were detected on HCT. BB demonstrated 83% sensitivity (95%[CI] 36-99%), 100% specificity (95%[CI] 88-100%), 100% PPV (95%[CI] 46-100%), 97% NPV (95%[CI] 82-99%), and 97% accuracy (95%[CI] 85-99%) for diagnosis of a skull fracture. BB detected 95% (19/20) of the skull fractures detected by CT. CONCLUSION: A black bone MRI sequence may provide high sensitivity and specificity for detection of skull fractures in pediatric patients with abusive head trauma.

Description

Keywords

Abusive head trauma, CT, MRI, Child Abuse, Child, Preschool, Female, Humans, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Infant, Magnetic Resonance Imaging, Male, Sensitivity and Specificity, Skull Fractures, Software, Tomography, X-Ray Computed

Journal Title

Neuroradiology

Conference Name

Journal ISSN

0028-3940
1432-1920

Volume Title

61

Publisher

Springer Science and Business Media LLC

Rights

All rights reserved
Sponsorship
Academy of Medical Sciences (Unknown)